Uplink Performance Approximation of Multicell Networks Based on Machine Learning 


Vol. 45,  No. 11, pp. 1855-1858, Nov.  2020
10.7840/kics.2020.45.11.1855


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  Abstract

In uplink multicell networks, the fractional power control (FPC) is a key feature of uplink operations and the FPC operation has to be considered in conjunction with the base station distribution and wireless channel for the uplink system level performance evaluation. Hence, this paper proposes the machine learning based performance evaluation method that can quickly provide the uplink SINR distribution. Also, the proposed method can be used for readily deriving the user experience SINR value and the simulation results demonstrate their accuracy.

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  Cite this article

[IEEE Style]

J. Kwon and T. Kwon, "Uplink Performance Approximation of Multicell Networks Based on Machine Learning," The Journal of Korean Institute of Communications and Information Sciences, vol. 45, no. 11, pp. 1855-1858, 2020. DOI: 10.7840/kics.2020.45.11.1855.

[ACM Style]

Jinwoo Kwon and Taesoo Kwon. 2020. Uplink Performance Approximation of Multicell Networks Based on Machine Learning. The Journal of Korean Institute of Communications and Information Sciences, 45, 11, (2020), 1855-1858. DOI: 10.7840/kics.2020.45.11.1855.

[KICS Style]

Jinwoo Kwon and Taesoo Kwon, "Uplink Performance Approximation of Multicell Networks Based on Machine Learning," The Journal of Korean Institute of Communications and Information Sciences, vol. 45, no. 11, pp. 1855-1858, 11. 2020. (https://doi.org/10.7840/kics.2020.45.11.1855)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880